Automatic learning of word transducers from examples". Fifth EACL

This paper describes the application of markovian teaming methods to the infer-ence of word transducers. We show how the proposed method dispenses from the difficult design of hand-crafted rules, al-lows the use of weighed non deterministic transducers and is able to translate words by taking into account their whole rather than by making decisions locally. These ar-guments are illustrated on two examples: morphological analysis and grapheme-to-phoneme transcription